Stabilization of amyloidogenic immunoglobulin light chains by small molecules.
Gareth J MorganNicholas L YanDavid E MortensonEnrico RennellaJoshua M BlundonRyan M GwinChung-Yon LinRobyn L StanfieldSteven J BrownHugh RosenTimothy P SpicerVirneliz Fernandez-VegaGiampaolo MerliniLewis E KayIan A WilsonJeffery W KellyPublished in: Proceedings of the National Academy of Sciences of the United States of America (2019)
In Ig light-chain (LC) amyloidosis (AL), the unique antibody LC protein that is secreted by monoclonal plasma cells in each patient misfolds and/or aggregates, a process leading to organ degeneration. As a step toward developing treatments for AL patients with substantial cardiac involvement who have difficulty tolerating existing chemotherapy regimens, we introduce small-molecule kinetic stabilizers of the native dimeric structure of full-length LCs, which can slow or stop the amyloidogenicity cascade at its origin. A protease-coupled fluorescence polarization-based high-throughput screen was employed to identify small molecules that kinetically stabilize LCs. NMR and X-ray crystallographic data demonstrate that at least one structural family of hits bind at the LC-LC dimerization interface within full-length LCs, utilizing variable-domain residues that are highly conserved in most AL patients. Stopping the amyloidogenesis cascade at the beginning is a proven strategy to ameliorate postmitotic tissue degeneration.
Keyphrases
- high throughput
- simultaneous determination
- small molecule
- end stage renal disease
- mass spectrometry
- newly diagnosed
- high resolution
- liquid chromatography
- induced apoptosis
- ejection fraction
- chronic kidney disease
- protein protein
- magnetic resonance
- peritoneal dialysis
- prognostic factors
- transcription factor
- magnetic resonance imaging
- heart failure
- left ventricular
- cell cycle arrest
- electronic health record
- computed tomography
- squamous cell carcinoma
- oxidative stress
- patient reported outcomes
- big data
- atrial fibrillation
- machine learning
- binding protein
- deep learning
- energy transfer